User Experience with Chinese Handwriting Input on Touch-Screen Mobile Phones

The Nintendo Switch is a popular hybrid portable gaming console that employs a novel modular design, enabling it to be played in multiple controller configurations: Handheld mode, left and right JoyCon Sticks, and the JoyCon Grip. However, there are notes of user complaints about the complexity of performing basic tasks as a result of the unintuitiveness of its user interface. This can result to poor gaming experience and may potentially affect customer buying decisions. To assess the affordance of the user interface design of the Nintendo Switch, a total of 16 Filipino participants, classified as either novice or expert users, based on familiarity with the Switch or other gaming consoles and their functionalities, were made to perform a predetermined set of tasks on navigating through the Nintendo Switch’s basic menus, and playing a racing game across different controller orientations. Affordance, overall usability, and gaming experience satisfaction were measured through 5-point Likert scales (5 being the highest) for affordance surveys, system usability scale (SUS) surveys, and in-task and post-task surveys, respectively. Separate sets of surveys were done for general navigation and gaming tasks. Additionally, quantitative measures of effectiveness (task completion success rates) and efficiency (time to successfully complete tasks) were taken for general navigation tasks, and compared between novice and expert users. Task efficiency rates were also compared to baseline values obtained from experienced Nintendo Switch users. Results show a significant difference between expert and novice users’ effectiveness rates, with expert users all successfully performing 73% of navigation tasks, compared to novice rates of 18%. Efficiency rates for both expert and novice participant groups consistently fell significantly behind baseline task completion times. Affordance survey results showed consistent ratings across different controller configurations for expert users, and high preference for JoyCon Grip and Handheld mode configurations for novice participants. Of all SUS scores, only Game Navigation for expert users scored above the 68-point threshold. Recommendations to improve the Nintendo Switch user interface affordance and overall user satisfaction were made.

Today, using communications devices such as simple and smart mobile phones has led man to face EMFs more. Thus is essential, measuring and comparing the emitted EMFs of simple mobile phones with that of smart phones. The EMFs of 2 simple mobile phones and 2 smart phones were measured by EMFs measurement portable equipment model HI-3603 in a ringing mode. Ultimately, the difference between electric and magnetic fields in simple and smart phones was evaluated by the ANOVA statistical test. The means of the electric fields of simple and smart mobile phones was 2.38±0.18 v/m and 1.9±0.18 v/m respectively. The means of magnetic fields of simple and smart mobile phones was 0.49±0.13 mG and 0.48±0.1 mG, respectively. The ratio of the mean of electric field in simple and smart phones to the standard limit (53.8 v/m) was 4.42% and 3.53% and also the ratio of the mean of electric field in simple and smart phones to the standard limit is 25.12% and 24.61%, respectively. Despite the fact that the mean of electric and magnetic fields of simple mobile phones is more than smart ones, the ANOVA statistical analysis shows that there is no significant difference between these two means (P value > 0.05). Despite the fact that EMFs in simple and smart phones are approximately equal or less than the standard limits, the safety notes shall be considered while using each of these devices.

Smart and cell phone with self-contained sensor such as accelerometer, gyroscopic and digital magnetic compass sensor have been popular. Combining certain algorithm and those sensors, it can estimate user’s activity, situation and even user’s absolute position. However, estimation of user’s activity, situation and user’s absolute position become difficult when once sensors posture and position are changing from original position in user’s motion. Also, according to stored, worn and handheld position and posture of those cell and smart phone are often changed. Therefore, we exclude estimation of user’s position and we focus to only estimation of user’s activity and situation for risk management. Basically, we design special classifier for detecting user’s unusual behavior and apply other user’s position data from internet to the results detected by the classifier which are combined wavelet transform and SVM. We assume that user’s unusual activity and situation can be detected by smart and cell phone with high accuracy.KeywordsActivity recognitionWearable computerSVMnearly fall incidentcell phone and smart phone

CogTool is a predictive evaluation tool for user interfaces. We wanted to apply CogTool to an evaluation of two mobile phones, but, at the time of writing, CogTool lacks the necessary (modeling baseline) observed human performance data to allow it to make accurate predictions about mobile phone use. To address this problem, we needed to collect performance data from both novice users’ and expert users’ interactions to plug into CogTool. Whilst novice users for a phone are easy to recruit, in order to obtain observed data on expert users’ performance, we had to recruit owners of our two target mobile phone models as participants. Unfortunately, it proved to be hard to find enough owners of each target phone model. Therefore we asked if multiple similar models that had matched interaction sequences could be treated as the same model from the point of view of expert performance characteristics. In this paper, we report an empirical experimental exercise to answer this question. We compared identical target task completion time for experts across two groups of similar models. Because we found significant differences in some of the task completion times within one group of models, we would argue that it is not generally advisable to consider multiple phone models as equivalent for the purpose of obtaining observed data for predictive modeling.KeywordsCognitive ModelCogToolEvaluationHuman Centered DesignHuman InterfaceMobile PhoneSystematizationUsability Test

Combined Expert and User-Driven Usability Assessment of Trauma Decision Support Systems Improves User-Centered Design

Background: Blended learning programs (BLPs) have been widely adopted across health professions education (HPE). To bolster their impact on learning outcomes, the usability of BLPs should be rigorously evaluated. However, there is a lack of reliable and validated tools to appraise this dimension of BLPs within HPE. The purpose of this investigation was to evolve a conceptual framework for usability evaluation in order to initially develop the Blended Learning Usability Evaluation – Questionnaire (BLUE-Q). Methods: After the completion of a scoping review, we conducted a qualitative descriptive study with seven purposefully selected international experts in usability and learning program evaluation. Individual interviews were conducted via videoconferencing, transcribed verbatim, and analyzed through thematic analysis. Results: Three themes were identified: (1) Consolidation of the multifaceted ISO definition of usability in BLPs within HPE; (2) Different facets of usability can assess different aspects of BLPs; (3) Quantitative and qualitative data are needed to assess the multifaceted nature of usability. The first theme adds nuance to a previously established HPE-focused usability framework, and introduces two new dimensions: ‘pedagogical usability’ and ‘learner motivation.’ The latter two provide guidance on structuring BLP evaluations within HPE. From this followed the development of the BLUE-Q, a new questionnaire that includes 55 Likert scale items and 6 open-ended questions. Conclusions: Usability is an important dimension of BLPs and must be examined to improve the quality of these interventions in HPE. As such, we developed a new questionnaire, solidly grounded in theory and the expertise of international scholars, currently under validation.

Objective:Cancer is a non-communicable disease that accounts for 71% of deaths globally. The prevalence of people living with cancer in Indonesia increased from 1.4/1000 population (2013) to 1.8/1,000 population (2018). This study aims to evaluate usability, user experience, and user feedback on the use of the Oncodoc m-health application. Methods: The research method uses mixed methods with a cross-sectional approach and online survey sampling techniques (677 respondents), in December 2021-January 2022 in Indonesia. The instruments used are the System Usability Scale and User Experience Questionnaire. The variables measured include the characteristics of respondents, usability, user experience, and responses to using applications qualitatively. Quantitative data were analysed descriptively and the User Experience Questionnaire’s analysis tool. Qualitative data were analysed thematically. Results:Evaluation of the usability of Oncodoc’s m-health application is in the “acceptable” category (70.88), and the adjective rating is in the “Good” category. Evaluations of the relative quality of user experience are in the “good” and “very good” types. The average user experience scale is (mean; SD): attractiveness (1.80; 0.99), perspicuity (1.82; 1.05), efficiency (1.78; 1.09), dependability (1.56; 1.01), stimulation (1.81; 1.06), and novelty (1.32; 1.10). The findings of this study are 1) the ability to accommodate user needs, 2) usage barriers, and 3) user expectations for the Oncodoc application. Conclusion:Overall, the Oncodoc m-health application is acceptable to users. We recommend developing a cancer early detection application with an approach that refers to user needs for further research.

ObjectiveTo assess (1) agreement between the ultrasonic cardiac output monitor (USCOM) 1A device for measurement of cardiac output in newborn infants and conventional echocardiography (ECHO), (2) repeatability of USCOM measurements...

The study investigated how mobile phones have been used for teaching and learning purposes in higher learning institutions in Tanzania. Specifically the study assessed how mobile phones facilitated the teaching and learning process, identified the mobile phone applications used for teaching and learning, determined the types of learning activities facilitated through mobile phones and assessed the common limitations of m%lea rning in at Sokoine University of Agriculture (SUA). The study employed a survey where teaching staff and students from faculties and institutes hosting academic programmes were involved. A total of 30 teaching staff and 40 students were randomly selected and included in the study. In%depth interviews, observations and questionnaire were used for data collection. It was found that majority of the respondents used their mobile phones for teaching and learning process. It was found that most respondents reported to use traditional mobile learning applications including text messages and calls. Few respondents had smart phones with a number of m%learning applications most of them being teaching staff. These were able to create upload, download and share academic resources through their smart phones while others recorded and stored files in their phones. It was also found that among teaching staff many were not aware of the capacity of their mobile phones such that they underutilized them. Costs associated with downloading multimedia content was another constraint which limited some respondents especially students from using phones for learning purposes. More than that, users were forced to use SMART/VISA cards for buying online mobile applications of which most respondents were not aware of.

The vision of user experience is making life of users of products as convenient as possible, especially during the interaction with a productor a service. An important aspect of perceived convenience is the user experience of a product. The visual design and especially the interaction design has a major influence on this perception. In order to achieve the vision, user experience experts apply different types of tasks. One type of task is to analyze how users carry out tasks and what user's needs or problems are. Another type of task is to design user experience solutions and other typical task type deals with carrying out usability evaluations in order to find problems in using software application. In the course of user experience activities, many data are being collected. Many of the collected data relates to certain activities of users. For the user experience area there exist just a few tools, which support typical tasks in different ways. None of the tools supports linking results of user experience work to user experience meta-data. Why is it a problem? The current tools do not support an access to user experience project data with generic search and filter criteria like case etc. This makes the access to user experience research data difficult and the comparison of user experience project data between different projects inefficient. In general, results of different user experience projects are difficult to reuse. The core idea of data pattern for allocating user experience Meta-Data to User Experience research data is to associate user experience project data with user experience meta-data. The data pattern considers associating user experience project data with user experience meta-data partially automatically and partially manually by the user. The key idea is that we want to reuse project data like the project sponsor, the application area, the industry, use cases etc. as user experience meta-data and assign them to user experience research data. The benefits of the data pattern are: Reusing results of user experience research projects. Making access to available results more efficient. Direct comparison of available results is supported and more efficient. UX Office is the typical instance for application.

Recently, smart phones have become a shining star in the mobile phone market, and the services provided by smart phones have significantly increased due to the advancements in hardware development and the great variety of user interfaces. Also, the stress of modern life has given more and more importance to the recreation and game industries. Therefore, this study aims to integrate a smart phone with a digital game so that the player can have the feel of real actions and enjoy the interaction during the game. By combining a digital game with a physical device, i.e., a mobile phone, the game player is provided with a richer gaming experience in which the mobile phone serves more than as a phone, and the game is more than tapping at a keyboard or clicking a mouse. The digital game in this study is about fishing. The fishing games on the market are typically played with a keyboard or a mouse, which nevertheless makes the games quite different from the real fishing experience. For example, the existing fishing games can hardly simulate the action of casting a fishing rod or reeling in the fish on the hook. In this study, a simulated setting is designed to mimic real situations so that digital interaction between the human and the computer in a human-computer interface can be assessed. A digital interactive game including both hardware and software is designed in this study, and whether the interactivity and the human-computer interface of the interactive game are acceptable by players is studied. According to questionnaire survey results, most players give positive evaluation to the combination of the mobile phone (i.e., hardware) and the digital game (i.e., software), and the more interactive the human-computer interface is, the stronger the interest and the greater the pleasure a player will feel in playing the game. Suggestions on how to improve the hardware and software design are also provided.

Although current athlete performance monitoring system designs undertaken within sports engineering and technology research have a strong focus on achieving functionality requirements, considerations on usability evaluation and testing during the design process are limited. Conventional design research highlights the importance of factoring usability at the heart of performance monitoring system designs like human-computer interfaces. Consequently, based on a user-centred approach, this research aimed to design a digital dashboard to optimise a scouting information flow within a professional basketball club and improve usability issues in the design by executing formative usability assessment approaches. Thematic analysis conducted on the data obtained from an initial semi-structured interview with the Head Coach of the club clarified dashboard functionality and design requirements, importance of the scouting process and information on potential system users. Thereafter, guided by the Build-Measure-Learn cycle in The Lean Startup framework, Minimum Viable Products (MVPs) of the dashboard were designed and 25 usability issues in the initial MVP were identified from heuristic evaluations conducted with three usability experts. Following system redesign, task-based think aloud usability testing sessions conducted with five coaches (i.e. users) at the club unravelled further nine usability issues in the dashboard, which were resolved by systematically pivoting to new MVPs during the iterative design process. Overall, this paper outlines a systematic approach to conducting formative usability assessment of sports technologies and highlights the importance of resolving specific usability issues present in technological systems like dashboards designed by practitioners embedded in applied sport environments.

We show how modern mobile phones (Weiser's tabs) can interact with their environment, especially large situated displays (Weiser's boards). Smart phones' emerging capabilities are fueling a rise in the use of mobile phones as input devices to such resources as situated displays, vending machines, and home appliances. Mobile phones' prevalence gives them great potential to be the default physical interface for ubiquitous computing applications. We survey interaction techniques that use mobile phones as input devices to ubiquitous computing environments. We use smart phone to describe an enhanced mobile phone. Our analysis blurs the line between smart phones and PDAs such as the Palm Pilot because the feature sets continue to converge.

Digital humanities platform has been developing rapidly. Using eye-tracking in usability evaluation can make a difference in user experience. In this paper we propose a gaze-experience model for usability evaluation on digital humanities platform, and select the “Digital Dunhuang” platform as the case study. A user experiment was carried out to verify the application value of the model through a large amount of eye-tracking and user experience data collection and analysis. We found that the features of eye-tracking (such as fixation and saccade) and those of user experience (such as satisfaction, efficiency and effectiveness) had correlations. Implications were also put forward to improve the usability of digital humanities platform and can be extended to similar platforms.

Objective To investigate the situation of college students using cell phones, and explore the relationship between College Students' cell phones addiction and self - control and the regulation effect of academic performance. Methods Using the entity questionnaire survey and the online questionnaire survey to research the situation of the college students' intelligent cell phones use and self control and the regulation effect of academic performance. Results The smartphone was very popular among college students, with 84.9% of college students using smartphones in the two surveys, and the smartphone addiction was about 10.6%. Smartphone addicts of college students related with origin of student (t= 2.31, P=0.022), and had no correlation with gender (t=-0.46, P=0.647), and major (t= 1.77, P=0.079). Students' phone addiction and self-control were positively correlated (r=0.506, P<0.01). The academic record ranking was regulated by self-control and college smart-phone using. Conclusion Cell phones are widely used among college students. Self-control positively related with cell phones and cell phone addiction, and the academic record ranking regulates the strength of relationship between the cell phones using and self control. Key words: Smartphone; Phone addiction; Self-control; Academic record